建築図面と状況グラフを活用したロボット自己位置推定
Robot Localization using Situational Graphs and Building Architectural Plans
建築図面から壁や部屋の幾何・意味・トポロジー情報を抽出して状況グラフを構築し、3D LiDARから得た壁面観測とパーティクルフィルタを組み合わせて建設現場でのロボット位置推定を行う手法を提案した。
著者: Muhammad Shaheer, Hriday Bavle, Jose Luis Sanchez-Lopez, Holger Voos
分類: cs.RO
原文アブストラクト
Robots in the construction industry can reduce costs through constant monitoring of the work progress, using high precision data capturing. Accurate data capturing requires precise localization of the mobile robot within the environment. In this paper we present our novel work on robot localization which extracts geometric, semantic as well as the topological information from the architectural plans in the form of walls and rooms, and creates the topological and metric-semantic layer of the Situational Graphs (S-Graphs) before navigating in the environment. When the robot navigates in the construction environment, it uses the robot odometry and the sensorial observations in the form of planar walls extracted from the 3D lidar measurements, to estimate its pose relying on a particle filter method, by exploiting the previously built situational graph and its available geometric, semantic and topological information. We validate our approach in both simulated and real datasets captured on actual on-going construction sites presenting state-of-the-art results when comparing it against traditional geometry based localization techniques.
